Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method, comprising: receiving, via at least one processor from a first plurality of users, requests for a networked service over at least one network; selecting, via the at least one processor in response to receiving the requests, a second plurality of users from the first plurality of users based on intrinsic service elements stored in association with the first plurality of users; matching, via the at least one processor according to a first scheme, users among the second plurality of users to form a first group of users based on environmental elements stored in association with the second plurality of users; matching, via the at least one processor according to a second scheme different from the first scheme, users among the second plurality of users to form a second group of users based on the environmental elements; and providing, via the at least one processor, a session of the networked service between the first group of users and the second group of users.
This invention relates to a system for dynamically grouping users in a networked service environment to facilitate interactions between distinct user groups. The problem addressed is the need to efficiently organize users into meaningful groups based on both intrinsic and environmental factors to enhance service delivery. The method involves receiving service requests from multiple users over a network. A subset of users is selected based on intrinsic attributes stored in association with each user, such as preferences, skills, or historical data. These selected users are then divided into two distinct groups using different matching schemes. The first group is formed by matching users according to a first scheme based on environmental elements, such as real-time conditions, location, or contextual data. The second group is formed using a second, different matching scheme applied to the same environmental elements. Finally, a session of the networked service is established between the two groups, enabling interaction or collaboration. The approach ensures that users are dynamically organized into optimized groups tailored to the service's requirements, improving engagement and efficiency.
2. The method of claim 1 , wherein: the intrinsic service elements are stored on a user-by-user basis; and the intrinsic service element of a user comprises information associated with at least one of a reception time of a request of the user, an option of the networked service set in association with the user, and a skill score set for the user according to a service process of the user.
This invention relates to personalized service management in networked systems, addressing the challenge of efficiently handling user-specific service elements to enhance service delivery. The method involves storing intrinsic service elements on a per-user basis, where each user's data includes details such as the reception time of their service request, networked service options configured for that user, and a skill score assigned based on the user's service process. These elements are dynamically managed to tailor services to individual user needs, improving response times, customization, and overall service quality. The system ensures that user-specific configurations and historical data are preserved and utilized to optimize future interactions, reducing redundancy and enhancing efficiency. By tracking request timings, service preferences, and performance metrics, the method enables adaptive service provisioning that aligns with user behavior and requirements. This approach is particularly useful in environments where personalized service delivery is critical, such as customer support, online platforms, or automated assistance systems. The stored data allows for real-time adjustments and long-term improvements in service accuracy and user satisfaction.
3. The method of claim 1 , wherein: the environmental elements are stored on a user-by-user basis; and the environmental element of a user comprises information associated with at least one of a nationality of the user, a race of the user, a gender of the user, an age of the user, a current access location of the user, a residential place of the user, a main access time of the user, a main access day of the user, a service start date of the user, a service use period of the user, an alma mater of the user, and a language of the user.
This invention relates to personalized data management systems that collect and store user-specific environmental elements to tailor services or content. The core problem addressed is the lack of granular, user-specific data that can be used to customize experiences, improve security, or enhance service delivery. The system captures and stores detailed user attributes on an individual basis, allowing for highly targeted applications. The stored environmental elements include demographic information such as nationality, race, gender, and age, as well as behavioral and contextual data like current access location, residential address, and primary usage times (day and time). Additional elements include service-related metrics like the user's service start date, duration of service use, and educational background (alma mater). Language preferences are also recorded. These attributes enable dynamic adjustments in services, content delivery, or security protocols based on the user's unique profile. By storing these elements on a per-user basis, the system ensures that each individual's data is distinct and can be leveraged for personalized interactions. This approach enhances user experience, improves service relevance, and supports adaptive security measures. The invention is particularly useful in applications requiring fine-grained user differentiation, such as targeted advertising, localized content delivery, or fraud detection.
4. The method of claim 1 , wherein matching users among the second plurality of users to form the first group of users or the second group of users based on the environmental elements stored in association with the second plurality of users comprises: determining environment weights with respect to pairs of users based on the environmental elements, each pair of users comprising the same reference user and a respectively different user from the second plurality of users; selecting a user pair from the pairs of users based on the environment weights; and matching the reference user to the respectively different user of the user pair.
This invention relates to a system for grouping users based on environmental elements, such as location, time, or activity context, to facilitate interactions or recommendations. The problem addressed is efficiently matching users who share similar environmental conditions to enhance collaboration, recommendations, or social interactions. The method involves analyzing a set of users and their associated environmental data, such as geographic location, time of day, or activity type. For each user, the system calculates environment weights that quantify similarity between that user and others in the group. These weights are derived from the environmental elements, ensuring that users with closely aligned contexts are prioritized. The system then selects user pairs based on these weights, where each pair includes a reference user and another user from the group. The reference user is matched with the most suitable counterpart from the remaining users, ensuring optimal grouping. This process repeats iteratively to form distinct groups, such as a first group for collaboration or a second group for targeted recommendations. The approach ensures that users are grouped dynamically based on real-time or historical environmental data, improving the relevance of interactions. This method is particularly useful in social networks, recommendation engines, or collaborative platforms where context-aware matching enhances user experience.
5. The method of claim 4 , wherein: the environmental elements are stored on a user-by-user basis; each environmental element comprises one or more items; and determining an environment weight with respect to pairs of users based on the environment elements comprises: determining, for each of the one or more items, an individual environmental element item weight based on a comparison of corresponding items associated with each user of a pair of users; and determining the environment weights based on the individual environmental element item weights.
This invention relates to a system for analyzing and comparing user environments, particularly in social or collaborative platforms, to enhance recommendations, matching, or personalized experiences. The problem addressed is the lack of granularity in assessing similarities or differences between users based on their environmental contexts, such as shared interests, activities, or digital footprints. The method involves storing environmental elements on a per-user basis, where each element contains one or more items (e.g., preferences, behaviors, or attributes). To quantify relationships between users, the system calculates environment weights by comparing corresponding items across pairs of users. For each item within an environmental element, an individual weight is determined based on the similarity or relevance of the item between the two users. These individual weights are then aggregated to produce an overall environment weight for the pair, reflecting their environmental alignment. This approach enables precise, item-level comparisons, allowing for more accurate user matching, recommendation systems, or collaborative filtering. The method ensures that environmental factors are evaluated comprehensively, improving the relevance of personalized outputs.
6. The method of claim 5 , wherein: the comparison corresponds to an inter-user difference in values of the corresponding items; and each value is established based on a determined valuation scheme of a corresponding item.
This invention relates to a method for analyzing inter-user differences in item valuations within a digital system. The method addresses the challenge of accurately comparing how different users perceive or assign value to the same items, which is critical for applications such as personalized recommendations, pricing strategies, or fairness assessments in digital platforms. The method involves comparing values assigned to items by different users, where each value is determined based on a predefined valuation scheme specific to the item. The valuation scheme defines how the item's value is calculated or derived, ensuring consistency in the comparison process. The comparison focuses on the differences in how users value the same item, allowing for insights into user preferences, biases, or behavioral patterns. The method may be part of a broader system that tracks user interactions with items, such as products, services, or digital content, and applies valuation schemes to quantify these interactions. The valuation schemes could be based on user ratings, engagement metrics, transaction history, or other relevant data points. By analyzing inter-user differences, the system can identify trends, personalize experiences, or optimize decision-making processes. This approach is particularly useful in scenarios where understanding user-specific valuations is essential, such as in e-commerce, social media, or recommendation engines. The method ensures that comparisons are meaningful by standardizing the valuation process while still capturing the nuances of individual user behavior.
7. The method of claim 4 , wherein matching the users among the second plurality of users into the first group of users or the second group of users based on the environmental elements stored in association with the second plurality of users further comprises: determining an average environment weight between the reference user and the respectively different user of the user pair; and matching another user with the reference user and the respectively different user based on the average environment weight.
This invention relates to user grouping systems that analyze environmental elements to categorize users into distinct groups. The problem addressed is the need for more accurate and context-aware user segmentation, particularly in scenarios where environmental factors influence user behavior or preferences. The method involves collecting environmental data associated with a plurality of users, such as location, time, weather, or device settings, and using this data to group users into at least two distinct categories. A reference user is selected, and pairs of users are compared based on their environmental data to determine similarity. For each user pair, an average environment weight is calculated, representing the degree of environmental similarity between the reference user and another user. This weight is then used to match additional users to the reference user and other users in the pair, ensuring consistent grouping based on environmental context. The method improves user segmentation by incorporating dynamic environmental factors, leading to more personalized and relevant groupings for applications like targeted advertising, social networking, or recommendation systems.
8. The method of claim 4 , further comprising: selecting one or more items of the environmental elements based on a service option set for each of the users of the second plurality of users, wherein the environment weights are determined based on the one or more items.
This invention relates to personalized environmental data processing for user groups, addressing the challenge of dynamically adapting environmental elements to individual user preferences within a shared system. The method involves analyzing environmental elements, such as sensory inputs or contextual data, and assigning weights to these elements based on user-specific service options. These service options define how each user interacts with or perceives the environment, allowing the system to prioritize or filter elements accordingly. The weighted elements are then used to generate or modify an environment tailored to each user's needs, ensuring personalized experiences while maintaining system efficiency. The method ensures that environmental data is processed in a way that aligns with user preferences, improving relevance and usability. This approach is particularly useful in applications like virtual reality, smart environments, or adaptive user interfaces where dynamic personalization is critical. The invention enhances user satisfaction by dynamically adjusting environmental elements based on predefined service options, ensuring that each user receives an optimized experience.
9. At least one non-transitory computer-readable storage medium comprising one or more instructions that, when executed, are configured to implement the method of claim 1 .
A system and method for automated data processing involves analyzing input data to identify patterns or anomalies. The process begins by receiving input data from one or more sources, which may include structured or unstructured data. The system then applies a preprocessing step to clean, normalize, or transform the data into a standardized format suitable for analysis. Next, the system applies one or more analytical techniques, such as statistical analysis, machine learning, or pattern recognition, to extract meaningful insights from the data. The results of the analysis are then output in a structured format, such as a report, visualization, or dataset, for further use. The system may also include a feedback mechanism to refine the analytical models based on user input or additional data. The method ensures efficient and accurate data processing, enabling better decision-making in applications such as fraud detection, predictive maintenance, or customer behavior analysis. The system is implemented using a computer-readable storage medium containing executable instructions that perform the described steps when executed by a processor.
10. A file distribution system configured to distribute, to a terminal, an installation file that, when executed by the terminal, is configured to install an application on the terminal, the application being configured to implement the method of claim 1 .
The file distribution system is designed for distributing software applications to terminals, such as computers or mobile devices, by providing installation files that, when executed, install an application on the terminal. The application, once installed, is configured to perform a specific method involving the generation of a first data set based on a first input, the generation of a second data set based on a second input, and the comparison of the first and second data sets to determine a similarity score. This similarity score is then used to generate a similarity result, which can be displayed or transmitted to another device. The system ensures that the installation file is properly distributed to the terminal, enabling the application to execute the method efficiently. The primary problem addressed by this system is the need for a reliable and automated way to distribute applications that can perform data comparison tasks, such as analyzing similarities between datasets, which may be useful in fields like data analysis, machine learning, or content recommendation. The system simplifies the deployment of such applications by handling the distribution and installation process, allowing users to quickly access the functionality without manual setup.
11. A file distribution system, comprising: a storage configured to store an installation file for an application; and a transmitter configured to transmit the installation file to a user terminal in response to reception of a request associated with the user terminal, wherein the application is configured to control the user terminal to receive a networked service via a server, and wherein the server is configured to: receive, from a first plurality of users, requests for the networked service over at least one network; select, in response to reception of the requests, a second plurality of users from the first plurality of users based on intrinsic service elements stored in association with the first plurality of users; match, according to a first scheme, users among the second plurality of users to form a first group of users based on environmental elements stored in association with the second plurality of users; match, according to a second scheme different from the first scheme, users among the second plurality of users to form a second group of users based on the environmental elements; and provide a session of the networked service between the first group of users and the second group of users.
The file distribution system is designed for managing and delivering application installation files to user terminals, enabling access to a networked service via a server. The system includes a storage component that holds installation files for applications and a transmitter that sends these files to user terminals upon request. The application, once installed, allows the user terminal to interact with a networked service hosted by a server. The server receives service requests from a first group of users over one or more networks. In response, it selects a second group of users from the first group based on intrinsic service elements associated with each user, such as user preferences, skills, or historical data. The server then matches users within this second group into two distinct groups using different matching schemes. The first scheme groups users based on environmental elements, such as location, time, or network conditions, while the second scheme uses a different approach to form a second group. The server then facilitates a session of the networked service between these two groups, enabling interaction or collaboration. This system ensures efficient distribution of applications and optimized user matching for networked services.
12. A system configured to provide a networked service to users over at least one network, the system comprising: at least one storage configured to store, on a user-by-user basis, intrinsic service elements and environmental elements; and at least one processor configured to: receive, via the at least one network, requests for the networked service from a first plurality of the users; select, in response to reception of the requests, a second plurality of the users from the first plurality of the users based on the intrinsic service elements; match, according to a first scheme, users of the second plurality of the users to form a first group of users based on the environmental elements; match, according to a second scheme different from the first scheme, users of the second plurality of users to form a second group of users based on the environmental elements; and provide, over the at least one network, a session of the networked service between the first group of users and the second group of users.
The system provides a networked service to users by dynamically grouping them based on stored user-specific data. The system operates in the domain of online services, addressing the challenge of efficiently organizing users into meaningful interactions. It stores intrinsic service elements (e.g., user preferences, skills, or profiles) and environmental elements (e.g., real-time context, location, or device status) for each user. When requests for the service are received, the system selects a subset of users based on their intrinsic attributes. These users are then divided into two distinct groups using different matching schemes applied to their environmental data. The first group is formed using one matching algorithm, while the second group is formed using a different algorithm. The system then facilitates a session where these two groups interact, enabling tailored and context-aware service delivery. This approach ensures that users are grouped optimally for their specific needs and circumstances, enhancing the service experience. The system dynamically adapts to user and environmental changes, improving engagement and service effectiveness.
13. The system of claim 12 , wherein the intrinsic service element of a user of the second plurality of the users comprises information corresponding to at least one of a reception time of a request of the user, an option of the networked service set in association with the user, and a skill score set for the user according to a service process of the user.
This system relates to a networked service platform that manages user interactions by tracking and utilizing intrinsic service elements associated with each user. The system addresses the challenge of efficiently routing and processing user requests within a networked service environment, where different users may have varying service requirements, preferences, or skill levels. The system includes a plurality of users categorized into at least two groups, where the intrinsic service elements of users in the second group include specific data points such as the reception time of a user's request, user-specific options or settings within the networked service, and a skill score assigned to the user based on their service process history. These elements help the system tailor service delivery, optimize resource allocation, and improve user experience by dynamically adjusting service parameters based on individual user attributes. The system may also incorporate additional features, such as user categorization, service request processing, and data analysis, to enhance service efficiency and personalization. By leveraging these intrinsic service elements, the system ensures that user requests are handled in a manner that aligns with their specific needs and capabilities, leading to more effective service outcomes.
14. The system of claim 12 , wherein the environmental element of a user of the second plurality of the users comprises information corresponding to at least one of a nationality of the user, a race of the user, a gender of the user, an age of the user, a current access location of the user, a residential place of the user, a main access time of the user, a main access day of the user, a service start date of the user, a service use period of the user, an alma mater of the user, and a language of a user.
This invention relates to a system for managing user access to services based on environmental elements associated with users. The system categorizes users into groups and assigns access permissions or restrictions based on predefined criteria. The environmental elements of users in a second group include demographic and behavioral data such as nationality, race, gender, age, current access location, residential place, main access time, main access day, service start date, service use period, alma mater, and language. The system uses this data to tailor access rules, ensuring that users receive appropriate permissions or restrictions based on their environmental context. This approach allows for dynamic and personalized access control, improving security and user experience by aligning service access with user-specific factors. The system may also integrate with other modules to refine access decisions further, ensuring adaptability to different use cases and regulatory requirements.
15. The system of claim 12 , wherein, to form the first group of users or the second group of users, the at least one processor is configured to: determine, based on the environment elements, environment weights for pairs of users from the second plurality of the users, each pair comprising a same reference user and a respectively different user from the second plurality of the users; select one pair of users from the pairs of users based on the environment weights; and match the same reference user to the respectively different user of the one pair of users.
This invention relates to a system for grouping users based on environmental factors to optimize interactions or outcomes. The system addresses the challenge of efficiently matching users in a way that accounts for environmental influences, such as physical or contextual conditions, to improve collaboration, recommendations, or other user interactions. The system includes at least one processor configured to analyze environment elements associated with a second plurality of users. These elements may include location, time, activity, or other contextual data. The processor calculates environment weights for pairs of users, where each pair consists of a reference user and a different user from the second plurality. These weights quantify the relevance or compatibility of each pair based on the environment elements. The system then selects one pair of users based on the highest or most favorable environment weights and matches the reference user to the other user in that pair. This matching process can be applied to form a first group of users or a second group of users, depending on the application. The system dynamically adjusts groupings based on real-time or evolving environmental conditions, ensuring optimal pairings for tasks such as team formation, content recommendations, or social interactions. The invention improves upon prior methods by incorporating environmental context into user matching, leading to more accurate and beneficial groupings.
16. The user matching system of claim 15 , wherein the at least one processor is further configured to: select one or more items of the environmental elements based on a service option set for each of the second plurality of the users; and determine the environment weights based on the one or more items.
This invention relates to a user matching system that improves the accuracy of user matching by incorporating environmental elements and their weights. The system addresses the problem of ineffective user matching in online platforms, where traditional methods often fail to account for contextual or situational factors that influence user behavior and preferences. The system collects environmental elements, such as time of day, location, device type, or network conditions, and assigns weights to these elements based on their relevance to the matching process. These weights are dynamically adjusted to enhance the precision of user matching. The system also selects specific environmental elements based on predefined service options for different users, ensuring that the matching process is tailored to individual needs. By integrating these weighted environmental factors, the system provides more accurate and context-aware user matching, improving user experience and engagement in online platforms. The invention is particularly useful in applications like social networking, e-commerce, or recommendation systems where contextual relevance is critical.
17. The method of claim 1 , further comprising: selecting a first advertisement based on environmental elements stored in association with users forming the first group of users; and providing the first advertisement to the users forming the first group of users.
This invention relates to targeted advertising systems that deliver advertisements to groups of users based on environmental elements associated with those users. The core problem addressed is the inefficiency of traditional advertising methods that do not account for real-time or contextual factors influencing user behavior. The system identifies a first group of users and selects a first advertisement tailored to that group by analyzing environmental elements stored in association with the users. These environmental elements may include location data, time of day, weather conditions, or other contextual factors that influence user preferences or behavior. The selected advertisement is then provided to the users in the first group, ensuring relevance and increasing engagement. The method may also involve determining a second group of users and selecting a second advertisement based on environmental elements associated with that group, then providing the second advertisement to the second group. This ensures that different user segments receive advertisements optimized for their specific contexts, improving ad performance and user experience. Additionally, the system may track user interactions with the advertisements to refine future targeting. This iterative process enhances the accuracy of ad selection over time, making the advertising more effective and personalized. The invention improves upon prior art by dynamically adjusting advertisements based on real-time environmental factors, leading to higher engagement and conversion rates.
18. The method of claim 17 , wherein the first advertisement is provided during the session to the users forming the first group of users.
A system and method for targeted advertising during user sessions involves dynamically grouping users based on their interactions with digital content. The method identifies a first group of users who have engaged with a specific content item, such as a video or article, during a session. The system then delivers a first advertisement to these users, tailored to their observed behavior. The advertisement is presented during the same session in which the content engagement occurred, ensuring relevance and timeliness. The method may also involve tracking additional user interactions, such as clicks or dwell time, to refine the targeting criteria. By analyzing these interactions, the system can further segment users into subgroups for more precise ad delivery. The approach improves ad relevance by leveraging real-time user behavior rather than relying solely on pre-existing user profiles or historical data. This dynamic grouping and immediate ad placement enhance engagement and conversion rates by aligning advertisements with the user's current interests. The system may also adjust ad delivery based on session duration or other contextual factors to optimize effectiveness.
19. The method of claim 18 , wherein a second advertisement is provided during the session to users forming the second group of users, the second advertisement being different from the first advertisement.
This invention relates to targeted advertising systems that dynamically adjust ad delivery based on user behavior during a session. The problem addressed is the inefficiency of static ad targeting, where users receive the same advertisement regardless of their engagement or lack thereof. The system monitors user interactions during a session to identify distinct groups of users. A first advertisement is initially provided to all users in the session. Based on user responses, such as clicks, dwell time, or other engagement metrics, the system categorizes users into at least two groups. A second, different advertisement is then delivered to users in the second group, tailored to their observed behavior. This approach improves ad relevance and conversion rates by adapting content in real-time. The system may also track additional user actions, such as purchases or navigation patterns, to further refine ad targeting. The method ensures that users who do not engage with the first ad receive an alternative, increasing the likelihood of a successful interaction. The invention applies to digital advertising platforms, including web and mobile environments, where dynamic content delivery enhances user experience and advertiser ROI.
20. The method of claim 1 , further comprising: matching, via the at least one processor according to a third scheme, the first group of users and the second group of users based on the environmental elements, wherein the third scheme is different from the first scheme.
This invention relates to user matching systems that analyze environmental elements to group users for interactions or recommendations. The problem addressed is the need for flexible and adaptive matching schemes that can dynamically adjust based on different contextual factors. The method involves processing data from at least one processor to group users into at least a first group and a second group. The grouping is performed according to a first scheme that evaluates environmental elements, such as location, time, or activity context. These environmental elements are extracted from user data, which may include sensor inputs, device logs, or user-provided information. The system then applies a second scheme to refine the grouping, where the second scheme may prioritize different environmental elements or use alternative weighting criteria compared to the first scheme. Additionally, the method includes a third matching scheme that further refines the grouping of the first and second user groups based on environmental elements. This third scheme is distinct from the first scheme, allowing for different matching criteria or algorithms to be applied. The system may use machine learning models or rule-based logic to determine the most appropriate matching scheme for a given context. The goal is to improve the relevance and accuracy of user groupings for applications such as social recommendations, collaborative tasks, or personalized content delivery.
21. The method of claim 1 , wherein: the first group of users comprises a first set of users and a second set of users; and the first scheme is applied differently to the first set of users than the second set of users.
This invention relates to user management systems, specifically methods for applying different schemes to distinct groups of users within a larger user base. The problem addressed is the need to customize user experiences or system interactions based on user segmentation, ensuring that different subsets of users receive tailored treatments or policies. The method involves dividing a first group of users into at least two subsets: a first set and a second set. A predefined scheme, such as a security protocol, access policy, or service tier, is then applied differently to each subset. For example, the first set may receive stricter authentication requirements, while the second set may have relaxed access controls. This differentiation allows for flexible user management, enabling system administrators to adapt policies based on user roles, risk levels, or other criteria without treating all users in the group uniformly. The method may also include additional steps such as monitoring user behavior, dynamically adjusting the scheme based on real-time data, or integrating with external systems to refine user segmentation. The goal is to enhance system efficiency, security, or user satisfaction by ensuring that each subset of users interacts with the system in a manner optimized for their specific needs. This approach is particularly useful in environments where user roles or risk profiles vary significantly within a single group.
22. The method of claim 1 , wherein, within a determined time period for matching users, a user among the second plurality of users is, based on the environmental elements, dynamically added to the first group of users and dynamically removed from the first group of users.
This invention relates to a dynamic user grouping system for matching users based on environmental elements. The system addresses the challenge of efficiently grouping users in real-time to facilitate interactions or services, such as social networking, ride-sharing, or collaborative tasks, by dynamically adjusting group membership based on changing environmental conditions. The method involves a first group of users and a second plurality of users. Environmental elements, such as location, time, weather, or user activity, are monitored to determine compatibility between users. Within a specified time period for matching, users from the second plurality are dynamically added to or removed from the first group based on these environmental factors. For example, a user may be added to the first group if their location aligns with the group's needs, but removed if conditions change, such as their activity level decreasing or their location shifting. The system ensures optimal group composition by continuously evaluating environmental data to maintain relevance and efficiency in user interactions. This dynamic adjustment enhances user experience by ensuring groups remain aligned with real-time conditions.
Unknown
August 20, 2019
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